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java.lang.Objectweka.classifiers.Classifier
weka.classifiers.MultipleClassifiersCombiner
weka.classifiers.RandomizableMultipleClassifiersCombiner
weka.classifiers.meta.Stacking
weka.classifiers.meta.Grading
public class Grading
Implements Grading. The base classifiers are "graded".
For more information, see
A.K. Seewald, J. Fuernkranz: An Evaluation of Grading Classifiers. In: Advances in Intelligent Data Analysis: 4th International Conference, Berlin/Heidelberg/New York/Tokyo, 115-124, 2001.
@inproceedings{Seewald2001, address = {Berlin/Heidelberg/New York/Tokyo}, author = {A.K. Seewald and J. Fuernkranz}, booktitle = {Advances in Intelligent Data Analysis: 4th International Conference}, editor = {F. Hoffmann et al.}, pages = {115-124}, publisher = {Springer}, title = {An Evaluation of Grading Classifiers}, year = {2001} }Valid options are:
-M <scheme specification> Full name of meta classifier, followed by options. (default: "weka.classifiers.rules.Zero")
-X <number of folds> Sets the number of cross-validation folds.
-S <num> Random number seed. (default 1)
-B <classifier specification> Full class name of classifier to include, followed by scheme options. May be specified multiple times. (default: "weka.classifiers.rules.ZeroR")
-D If set, classifier is run in debug mode and may output additional info to the console
Constructor Summary | |
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Grading()
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Method Summary | |
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double[] |
distributionForInstance(Instance instance)
Returns class probabilities for a given instance using the stacked classifier. |
java.lang.String |
getRevision()
Returns the revision string. |
TechnicalInformation |
getTechnicalInformation()
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on. |
java.lang.String |
globalInfo()
Returns a string describing classifier |
static void |
main(java.lang.String[] argv)
Main method for testing this class. |
java.lang.String |
toString()
Output a representation of this classifier |
Methods inherited from class weka.classifiers.meta.Stacking |
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buildClassifier, getCapabilities, getMetaClassifier, getNumFolds, getOptions, listOptions, metaClassifierTipText, numFoldsTipText, setMetaClassifier, setNumFolds, setOptions |
Methods inherited from class weka.classifiers.RandomizableMultipleClassifiersCombiner |
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getSeed, seedTipText, setSeed |
Methods inherited from class weka.classifiers.MultipleClassifiersCombiner |
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classifiersTipText, getClassifier, getClassifiers, setClassifiers |
Methods inherited from class weka.classifiers.Classifier |
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classifyInstance, debugTipText, forName, getDebug, makeCopies, makeCopy, setDebug |
Methods inherited from class java.lang.Object |
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equals, getClass, hashCode, notify, notifyAll, wait, wait, wait |
Constructor Detail |
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public Grading()
Method Detail |
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public java.lang.String globalInfo()
globalInfo
in class Stacking
public TechnicalInformation getTechnicalInformation()
getTechnicalInformation
in interface TechnicalInformationHandler
getTechnicalInformation
in class Stacking
public double[] distributionForInstance(Instance instance) throws java.lang.Exception
distributionForInstance
in class Stacking
instance
- the instance to be classified
java.lang.Exception
- if instance could not be classified
successfullypublic java.lang.String toString()
toString
in class Stacking
public java.lang.String getRevision()
getRevision
in interface RevisionHandler
getRevision
in class Stacking
public static void main(java.lang.String[] argv)
argv
- should contain the following arguments:
-t training file [-T test file] [-c class index]
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